Associations of traffic safety attitudes and ticket fixing behaviours with the crash history of Pakistani drivers
Bibliographic record
Abstract
The study assessed whether traffic safety attitudes and ticket fixing behaviours were associated with the crash history. A total of 4018 male drivers from Lahore city participated in this cross sectional study. Most were aged 18-30 years (58.7%, n = 2362), 71.9% (n = 2887) received a traffic ticket, 66.5% (n = 2672) reported previous traffic ticket fixing and 71.3% (n = 2865) considered crashes as being the will of God. Crash history was reported by 95.4% (n = 3821) of drivers, and 58.2% of them reported being involved in a road traffic crash. The likelihood of reporting a previous crash was higher in those who had received a traffic sign violation ticket [adjusted odds ratio (aOR) = 1.40; 95% confidence interval (95%CI) = 1.15-1.72], were involved in traffic ticket fixing (aOR = 1.28; 95%CI = 1.07-1.53), and considered crashes as will of God (aOR = 1.86; 95% CI = 1.57-2.22). These results suggested the need for improving traffic enforcement monitoring and safety education in Pakistan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".